Process simulation can be used to model one or more process critical to the operation and success of an organization. Generally, processing simulation can take on various forms from physical modeling of existing or proposed processes to virtual modeling and simulation using various software tools and computing applications. The commonality among existing approaches is the ability to identify the strength and weaknesses of a given process before expending the time and resources in implementing the given process. The foresight that results from process simulation can be used to derive various benefits including but not limited to competitive business advantages, optimization of process resources (e.g., labor, time, money, raw materials, facilities, etc.), and optimization of process workflow. Process simulation spans various industries and is utilized in numerous contexts. Ranging from manufacturing process simulation to business operations and management process simulation, process simulation can offer insightful data used in decision making.
Currently, there are various computing and non-computing process simulation tools and utilities available to assist in performing process simulation. For example, iGrafx and SImProcess are computing process simulation tools that allow participating users the ability to virtually run desired processes to identify the processes strengths and weaknesses. Current implementations, however, can be cumbersome and resource intensive requiring participating users to model many aspects of the process being simulated. Moreover, given the user-defined modeling architecture of current process simulation processes there is apt to be more frequent errors in the definition of the simulation model. Such errors can result in non-realistic process simulation (i.e., the simulated process does not represent the actual process) and, correspondingly, errant process analysis data.